X-Git-Url: https://adrianiainlam.tk/git/?a=blobdiff_plain;f=baseband.m;h=d6f0f1b7fb6aee70bc0af787f9c32eb0daf19979;hb=6a44550d735c954aef8333e48a481670d85fd505;hp=faf37f92fc3f3e64219d6cbea1910b99d0fe9ba3;hpb=8449f934a70109b11c63373ca459dce3ac854cec;p=4yp.git

diff --git a/baseband.m b/baseband.m
index faf37f9..d6f0f1b 100644
--- a/baseband.m
+++ b/baseband.m
@@ -10,30 +10,16 @@ function baseband(rolloff, M, numSymbs)
     rolloff = 0.5;
   end
 
-
   %% https://www.mathworks.com/help/comm/examples/passband-modulation-with-adjacent-channel-interference.html
   Rsym = 1e6; % symbol rate (sym/sec)
 
   span = 6; % filter span
-  sps = 4; % samples per symbol
-
-  txFilter = comm.RaisedCosineTransmitFilter...
-                 ('Shape', 'Square root', ...
-                  'RolloffFactor', rolloff, ...
-                  'FilterSpanInSymbols', span, ...
-                  'OutputSamplesPerSymbol', sps);
-  rxFilter = comm.RaisedCosineReceiveFilter...
-                 ('Shape', 'Square root', ...
-                  'RolloffFactor', rolloff, ...
-                  'FilterSpanInSymbols', span, ...
-                  'InputSamplesPerSymbol', sps, ...
-                  'DecimationFactor', 1);
+  sps = 2; % samples per symbol
 
   fs = Rsym * sps; % sampling freq (Hz)
 
   t = (0 : 1 / fs : numSymbs / Rsym + (1.5 * span * sps - 1) / fs)';
 
-
   EbN0_db = 0:0.2:10;
   EbN0 = 10 .^ (EbN0_db ./ 10);
   Es = 1;
@@ -49,56 +35,30 @@ function baseband(rolloff, M, numSymbs)
   data = randi([0 M - 1], numSymbs, 1);
   modData = pskmod(data, M, 0, 'gray');
 
-  xBaseband = txFilter([modData; zeros(span, 1)]);
-
-
+  xBaseband = txFilter(modData, rolloff, span, sps);
 
   for i = 1:plotlen
-    snr = EbN0_db(i) + 10 * log10(log2(M)) - 10 * log10(sps); % why sps?
+    snr = EbN0_db(i) + 10 * log10(log2(M)) - 10 * log10(sps);
     noiseEnergy = 10 ^ (-snr / 10);
 
     yBaseband = awgn(xBaseband, snr, 'measured');
 
-    rBaseband = rxFilter([yBaseband; zeros(span, 1)]);
-    %% truncate filter transients
-    rBaseband = rBaseband(span * sps / 2 + 1 : end);
-    %% normalize to unit energy
-    rBasebandEnergy = sum(abs(rBaseband) .^ 2) / numSymbs;
-    rBaseband = rBaseband .* sqrt((1 + noiseEnergy) / rBasebandEnergy);
+    rBaseband = rxFilter(yBaseband, rolloff, span, sps);
 
     rSampled = rBaseband(sps*span/2+1:sps:(numSymbs+span/2)*sps);
-
     demodData = pskdemod(rSampled, M, 0, 'gray');
-
     [bitErrors, ber(i)] = biterr(data, demodData);
   end
 
-  fig1 = figure(1);
+  figure(1);
   clf;
 
   %% Plot simulated results
   semilogy(EbN0_db, ber, 'r', 'LineWidth', 2);
   hold on;
 
-  %% Plot theoretical curve
-  %% BPSK: bit error when noise Nr > sqrt(Eb)
-  %%   Pr(Nr > sqrt(Eb))
-  %% = Pr(Z > sqrt(Eb) / sqrt(N0/2))
-  %%
-  %% QPSK = 2 BPSKs, one real and one imaginary, each with one bit
-  %% so BER is the same as BPSK (assuming Gray code)
-  if M == 2 || M == 4
-    ber_th = qfunc(sqrt(2 * EbN0));
-    semilogy(EbN0_db, ber_th, 'b', 'LineWidth', 1);
-    legend('Simulated', 'Discrete');
-  else
-    %% Approximation: J.G. Proakis and M. Salehi, 2000, Contemporary
-    %%                Communication Systems using MATLAB (Equations
-    %%                7.3.18 and 7.3.19), Brooks/Cole.
-    ber_ap = 2 * qfunc(sqrt(EbN0 * log2(M) * 2) * sin(pi / M)) / log2(M);
-    semilogy(EbN0_db, ber_ap, 'b', 'LineWidth', 1);
-    legend('Simulated', 'Discrete');
-  end
+  theoreticalPSK(EbN0_db, M, 'b', 'LineWidth', 1);
+  legend('Simulated', 'Discrete');
 
   title(strcat(num2str(M), '-PSK with Gray code'));
   grid on;
@@ -106,10 +66,4 @@ function baseband(rolloff, M, numSymbs)
   ylabel('BER');
 
   formatFigure;
-  %saveas(gcf, strcat('BER_SNR_', num2str(M), 'PSK_', num2str(numSymbs), ...
-  %                   '.svg'));
-
-  %scatterplot(rxFilt);
-  %eyediagram(rxFilt, sps);
-
 end